This research identifies factors that distinguish rural women who have migrated to Bangkok for the purpose of enhancing their economic wellbeing by engaging in the sex industry and those who have stayed in their rural communities and are not engaged in the sex industry. The research used primary data collected through interviews in the red light districts of Bangkok and Pattaya and in villages in the rural provinces of Buriram, Udon Thani, Sakon Nakhon, Chayaphum and Khon Kaen in Thailand. A total of 100 respondents provided information for the study: 55 percent from the red light districts and the remainder from the provinces. The data were analyzed using logit regression modeling approach as well as statistical analysis. The statistical analysis provided the descriptive statistics of the respondents and an overview of the data. The logit regression modeling approach facilitated the estimation of the responses of the probability of working in the red light entertainment districts to specified demographic and psychographic variables.

The pseudo R-square of the logit model was 46.2 percent for the base model, which included age, marital status, number of male and female siblings respectively, birth position and number of children, education, financial responsibility and average monthly age. The results indicated that marital status was significant at the 1 percent level, exhibiting a marginal effect of about -35.2 percent. That is, when the marital status of a respondent changed from unmarried (0) to married (1), the probability of sex industry participation decreased by about 35 percent.

Assessing the effect only among respondents with children, the results are not very different from the base model. The pseudo R-square for this model – which is the same as the base model, except that it has Teen Mother as a variable – was 61.4 percent with a total number of observations of 78 instead of the original 100. This implies that about 22 respondents did not have any children. In this model, the marital status variable is significant at the 1 percent level as was the number of female siblings. The average monthly wage is significant at the 5 percent level, with a 1000 Thai Baht increase in wages leading to a marginal 0.01 percent decline in the probability of sex industry participation. Education, under this model, is statistically significant at the 10 percent level, with another year of education decreasing the probability of sex industry participation by 2.5 percent.

The foregoing provides some clear policy direction. Specific efforts may be invested in enhancing the education of women in Thailand, which is expected to increase their economic situation. However, this expectation would not materialize if investments are not made to enhance the economic opportunities available to women across the economic spectrum. Perhaps most importantly, however, this study shows that incremental improvement in educational and economic opportunities for rural women alone may not achieve lasting results if cultural paradigms regarding marriage, relational fidelity and imbalanced socio-cultural obligations of daughters are not addressed in tandem.